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Sentic Computing A Commonsensebased Framework For Conceptlevel Sentiment Analysis 1st Edition Erik Cambria

  • SKU: BELL-5354336
Sentic Computing A Commonsensebased Framework For Conceptlevel Sentiment Analysis 1st Edition Erik Cambria
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Sentic Computing A Commonsensebased Framework For Conceptlevel Sentiment Analysis 1st Edition Erik Cambria instant download after payment.

Publisher: Springer International Publishing
File Extension: PDF
File size: 4.16 MB
Pages: 196
Author: Erik Cambria, Amir Hussain (auth.)
ISBN: 9783319236537, 9783319236544, 3319236539, 3319236547
Language: English
Year: 2015
Edition: 1

Product desciption

Sentic Computing A Commonsensebased Framework For Conceptlevel Sentiment Analysis 1st Edition Erik Cambria by Erik Cambria, Amir Hussain (auth.) 9783319236537, 9783319236544, 3319236539, 3319236547 instant download after payment.

This volume presents a knowledge-based approach to concept-level sentiment analysis at the crossroads between affective computing, information extraction, and common-sense computing, which exploits both computer and social sciences to better interpret and process information on the Web.
Concept-level sentiment analysis goes beyond a mere word-level analysis of text in order to enable a more efficient passage from (unstructured) textual information to (structured) machine-processable data, in potentially any domain.
Readers will discover the following key novelties, that make this approach so unique and avant-garde, being reviewed and discussed:
• Sentic Computing's multi-disciplinary approach to sentiment analysis-evidenced by the concomitant use of AI, linguistics and psychology for knowledge representation and inference
• Sentic Computing’s shift from syntax to semantics-enabled by the adoption of the bag-of-concepts model instead of simply counting word co-occurrence frequencies in text
• Sentic Computing's shift from statistics to linguistics-implemented by allowing sentiments to flow from concept to concept based on the dependency relation between clauses
This volume is the first in the Series Socio-Affective Computing edited by Dr Amir Hussain and Dr Erik Cambria and will be of interest to researchers in the fields of socially intelligent, affective and multimodal human-machine interaction and systems.

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